Surgical robots have high requirements for intraoperative registration. Relying solely on their built-in navigation and positioning functions is far from enough—combining intraoperative 3D CT imaging is essential to enhance navigation accuracy.
Unlike the spiral CT scanners used in radiology departments, intraoperative 3D CT typically relies on cone-beam CT (CBCT) systems, most commonly 3D C-arms and O-arms.
How does intraoperative 3D CT assist surgical robots in surgical navigation? The following content uses intraoperative 3D mobile C-arm imaging (PLX C7600) in spine surgery as an example to introduce four key workflow steps.
How Intraoperative 3D CT Assists Surgical Robots
(1) Intraoperative Image Acquisition
Navigation during surgery can be performed using CT or MRI images. In orthopedic surgery, where precise visualization of bony structures is crucial, intraoperative CT imaging is more widely used than MRI. Mobile intraoperative CT systems are particularly favored.
Image-based navigation technology using fluoroscopy and CT is similar. Multiple intraoperative fluoroscopic images can be uploaded to the workstation for 3D reconstruction. The latest fluoroscopy-based navigation technologies can even perform real-time reconstruction using preoperative CT data, allowing surgeons to visualize the patient’s true anatomical structures during surgery.
(2) Motion Tracking
Surgical navigation requires a motion capture system to track the spatial movement of surgical instruments and display their position changes on the screen in real time. In spine surgery, optical tracking systems are the most commonly used.
Optical motion tracking relies on cameras and triangulation to determine the precise spatial position of objects. To ensure navigation accuracy, the optical cameras should remain unobstructed throughout surgery.
With motion tracking, the navigation system can continuously identify and track an instrument’s translation and rotation within the coordinate system.
(3) Image Registration
Before surgery begins, the navigation system must associate the anatomical structures in the intraoperatively acquired images with the patient’s actual anatomy, enabling image-guided surgery. Image registration aligns the coordinate system of the acquired images with the tracking system, essentially creating a “map” for navigation guidance.
For example, the Perlove spinal surgical navigation system automatically performs image coordinate construction and system coordinate registration by tracking the C-arm’s 3D acquisition trajectory. This method is unaffected by image quality. Compared with fiducial-based registration, trajectory-based registration offers higher accuracy, fewer steps, and greater operational efficiency.
(4) Image Visualization
Once registration is completed, the navigation system overlays the virtual representation of the surgical instrument onto the intraoperative 3D images. As the surgeon moves the actual instrument, its virtual counterpart moves synchronously on the CT images in real time.
By observing the navigation display, surgeons can continuously understand the spatial relationship between the instrument and the patient’s anatomy. This information is crucial—it allows the surgeon to accurately assess the distance between the instrument and the target location and follow the pre-planned surgical path with precision.
